I would love to one day be a professional sports data analyst. I know I'm a long ways off, but with the encouragement of my professor and research advisor, I have decided to start posting some of my statistical analysis here on this blog! Bear with me as I have presented my research before, but I have never put it in writing.
Per game statistics are great, but I find that they make it difficult to compare players directly with other players. The difference in minutes and minutes per game leave us guessing how these players compare with each other (watching the game helps, but I'll get to that a little later). One player that I have found interest in lately is Payton Dastrup on the BYU Men's Basketball Team. Anyone who knows me will not be surprised by this, as I am a major BYU fan.
Dastrup is intriguing to me for many reasons. Many BYU fans have said on social media that they believe he deserves more playing time than he gets, this situation is interesting because the coaches obviously disagree. As I started this research, I wanted to see if Dastrup is actually the scorer that fans believe him to be and if he is, why the coaches don't seem to play him as much as other players who play his position.
The first step to all of this was to get the season data for BYU. I grabbed the per game and season statistics. The per game statistics are shown below.
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| Braiden Shaw | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Evan Troy | 12 | 1.5 | 0.5 | 0.2 | 0.2 | 0.1 | 0 | 0 | 0.25 | 0.667 | 0 |
| Kajon Brown | 9 | 4.3 | 0.8 | 0.1 | 0.1 | 0.2 | 0 | 0.4 | 0.5 | 0.6 | 0 |
| Rylan Bergersen | 23 | 3.4 | 1 | 0.4 | 0.1 | 0.1 | 0 | 0.1 | 0.563 | 0.75 | 0.429 |
| Payton Dastrup | 31 | 7.4 | 3.2 | 1.8 | 0.5 | 0.3 | 0.4 | 0.6 | 0.522 | 0.667 | 0.462 |
| McKay Cannon | 28 | 19.1 | 3.6 | 1.2 | 1.5 | 1 | 0 | 0.8 | 0.418 | 0.8 | 0.326 |
| Luke Worthington | 34 | 14.6 | 4.3 | 2.8 | 0.5 | 0.4 | 0.2 | 0.6 | 0.487 | 0.596 | 0 |
| Zac Seljaas | 34 | 20 | 5.2 | 1.9 | 1.4 | 0.4 | 0.3 | 0.8 | 0.464 | 0.821 | 0.307 |
| Jahshire Hardnett | 34 | 26.8 | 5.9 | 2.7 | 2 | 0.7 | 0.1 | 1.7 | 0.442 | 0.807 | 0.326 |
| Dalton Nixon | 23 | 17.3 | 6 | 3 | 1.3 | 0.6 | 0.2 | 0.8 | 0.527 | 0.72 | 0.238 |
| TJ Haws | 34 | 33.9 | 11.8 | 2.8 | 4.2 | 1.2 | 0.3 | 1.9 | 0.411 | 0.837 | 0.323 |
| Elijah Bryant | 34 | 34.6 | 17.9 | 6.2 | 2.3 | 1.3 | 0.6 | 2.2 | 0.491 | 0.873 | 0.412 |
| Yoeli Childs | 34 | 34.1 | 18 | 8.6 | 2.2 | 0.9 | 1.9 | 2.2 | 0.548 | 0.643 | 0.318 |
I experienced the same frustration that I mentioned earlier with comparing stats across players who play very different amounts of time per game. So, I took some of the per game statistics and some of the season statistics and converted them to statistics that are per 40 minutes. This table shows the players' average numbers per 40 minutes, instead of their per games averages. The change from per game to per 40 minutes makes the players easier to directly compare with each other. For instance, sometimes it is difficult to compare the production of players that only average 15 minutes per game to players that average 35 minutes per game.
Although the players' averages should be more comparable with the per 40 minute statistics, it is important to remember that fatigue and level of competition may affect the player's averages, particularly bringing the starters' averages down. I have included the overall minutes from the season to show how many minutes the players' averages are based on (more minutes means the averages are more precise). The per 40 minute statistics are shown below.
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| Braiden Shaw | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Kajon Brown | 39 | 4.3 | 7.179 | 0.5 | 0.6 | 0 | 1.026 | 1.026 | 0 | 4.103 | 2.051 |
| McKay Cannon | 536 | 19.1 | 7.537 | 0.418 | 0.8 | 0.326 | 3.134 | 2.463 | 0.075 | 1.567 | 2.015 |
| Jahshire Hardnett | 910 | 26.8 | 8.747 | 0.442 | 0.807 | 0.326 | 2.989 | 4.043 | 0.088 | 2.505 | 1.011 |
| Zac Seljaas | 679 | 20 | 10.368 | 0.464 | 0.821 | 0.307 | 2.828 | 3.711 | 0.530 | 1.591 | 0.766 |
| Luke Worthington | 498 | 14.6 | 11.727 | 0.487 | 0.596 | 0 | 1.285 | 7.550 | 0.562 | 1.526 | 0.964 |
| Rylan Bergersen | 78 | 3.4 | 12.308 | 0.563 | 0.75 | 0.429 | 1.026 | 4.615 | 0 | 1.538 | 1.026 |
| Evan Troy | 18 | 1.5 | 13.333 | 0.25 | 0.667 | 0 | 4.444 | 4.444 | 0 | 0 | 2.222 |
| TJ Haws | 1152 | 33.9 | 13.889 | 0.411 | 0.837 | 0.323 | 4.965 | 3.264 | 0.313 | 2.222 | 1.424 |
| Dalton Nixon | 399 | 17.3 | 13.935 | 0.527 | 0.72 | 0.238 | 3.008 | 6.917 | 0.501 | 1.905 | 1.404 |
| Payton Dastrup | 229 | 7.4 | 17.118 | 0.522 | 0.667 | 0.462 | 2.445 | 9.956 | 2.271 | 3.319 | 1.572 |
| Elijah Bryant | 1178 | 34.6 | 20.645 | 0.491 | 0.873 | 0.412 | 2.683 | 7.199 | 0.645 | 2.581 | 1.494 |
| Yoeli Childs | 1158 | 34.1 | 21.174 | 0.548 | 0.643 | 0.318 | 2.591 | 10.052 | 2.176 | 2.625 | 1.036 |
Now that I have the per 40 minute statistics, it's time to see just how productive Dastrup is while he's in the game. In order to determine Dastrup's (and the rest of the team's) offensive efficiency is, I decided to use two non-traditional statistics. The first statistic that I am going to show you is effective field goal percentage. Typically, big men have an advantage in field goal percentage because they shoot so many shots close to the basket, as opposed to guards who do slash to the basket, but tend to shoot more three point shots than big men.
Effective field goal percentage weights three point shots, so that they are worth 1.5 times more than two point shots. Below are the shooting statistics for the BYU Men's Basketball Team, sorted by effective field goal percentage. I have removed the players who have played less than 100 minutes as their averages are accurate, but are not as precise as the rest of the players.
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| Payton Dastrup | 229 | 7.4 | 0.612 | 1.264 | 11.703 | 4.541 |
| Elijah Bryant | 1178 | 34.6 | 0.596 | 1.317 | 13.209 | 6.757 |
| Yoeli Childs | 1158 | 34.1 | 0.564 | 1.179 | 15.199 | 1.520 |
| Dalton Nixon | 399 | 17.3 | 0.554 | 1.209 | 9.323 | 2.105 |
| Zac Seljaas | 679 | 20 | 0.546 | 1.155 | 8.247 | 4.418 |
| McKay Cannon | 536 | 19.1 | 0.513 | 1.122 | 5.896 | 3.433 |
| Jahshire Hardnett | 910 | 26.8 | 0.490 | 1.099 | 6.857 | 2.022 |
| TJ Haws | 1152 | 33.9 | 0.488 | 1.084 | 11.319 | 5.382 |
| Luke Worthington | 498 | 14.6 | 0.487 | 1.042 | 9.237 | 0 |
As can be seen by the table shown above, Dastrup leads the team in effective field goal percentage, followed by Elijah Bryant and Yoeli Childs, BYU's star players. One thing that may be affecting his percentage is that lately, he has been playing in "garbage time," which probably brings his percentage up. However, "garbage time" realistically does not increase his percentage enough for him to not be near the top of the team regularly. He seems to be shooting really well, like one would assume after watching him play.
The next statistic that I am going to look at is also mentioned above, points created. Points created assesses how well a player scores on a per possession basis, including field goals and free throws. David Locke of the Utah Jazz is pioneering a similar statistic. Locke calls his statistic "points above average created," or PAAC. He takes the statistic as I've calculated it, but then he subtracts the NBA's average from this statistic for each player. I don't currently have the NCAA average, so I simply have the point created for each player, without subtracting an average. The concept is that you can compare each player on the team by how many points they create per possession that they use a scoring opportunity. The next table is the team sorted by points created.
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| Elijah Bryant | 1178 | 34.6 | 1.317 | 2.581 | 2.683 |
| Payton Dastrup | 229 | 7.4 | 1.264 | 3.319 | 2.445 |
| Dalton Nixon | 399 | 17.3 | 1.209 | 1.905 | 3.008 |
| Yoeli Childs | 1158 | 34.1 | 1.179 | 2.625 | 2.591 |
| Zac Seljaas | 679 | 20 | 1.155 | 1.591 | 2.828 |
| McKay Cannon | 536 | 19.1 | 1.122 | 1.567 | 3.134 |
| Jahshire Hardnett | 910 | 26.8 | 1.099 | 2.505 | 2.989 |
| TJ Haws | 1152 | 33.9 | 1.084 | 2.222 | 4.965 |
| Luke Worthington | 498 | 14.6 | 1.042 | 1.526 | 1.285 |
Points created favors Elijah Bryant as the top on the team, partially because he gets to the free throw line at a much higher rate than Payton Dastrup. Yoeli Childs is the only player who gets to the line more often than Bryant. However, Payton Dastrup is still at the top, showing that when he is on the court. He creates a lot of points per possessions that he finishes. Now, it's time to see why Dastrup may not be playing that many minutes. Although he seems to be efficient on offense, he averages a lot of turnovers. Below is the final table for this post, it shows the team sorted by turnovers.
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| Payton Dastrup | 7.4 | 3.319 | 17.118 | 0.522 | 0.667 | 0.462 | 9.956 | 2.271 | 1.572 | 2.445 |
| Yoeli Childs | 34.1 | 2.625 | 21.174 | 0.548 | 0.643 | 0.318 | 10.052 | 2.176 | 1.036 | 2.591 |
| Elijah Bryant | 34.6 | 2.581 | 20.645 | 0.491 | 0.873 | 0.412 | 7.199 | 0.645 | 1.494 | 2.683 |
| Jahshire Hardnett | 26.8 | 2.505 | 8.747 | 0.442 | 0.807 | 0.326 | 4.044 | 0.088 | 1.011 | 2.989 |
| TJ Haws | 33.9 | 2.222 | 13.889 | 0.411 | 0.837 | 0.323 | 3.264 | 0.313 | 1.424 | 4.965 |
| Dalton Nixon | 17.3 | 1.905 | 13.935 | 0.527 | 0.72 | 0.238 | 6.917 | 0.501 | 1.404 | 3.008 |
| Zac Seljaas | 20 | 1.591 | 10.368 | 0.464 | 0.821 | 0.307 | 3.711 | 0.530 | 0.766 | 2.828 |
| McKay Cannon | 19.1 | 1.567 | 7.537 | 0.418 | 0.8 | 0.326 | 2.463 | 0.075 | 2.015 | 3.134 |
| Luke Worthington | 14.6 | 1.526 | 11.727 | 0.487 | 0.596 | 0 | 7.550 | 0.562 | 0.964 | 1.285 |
This table shows that Payton Dastrup leads the team in turnovers. I believe that a lot of fans want to see Dastrup play more because he shoots well and rebounds near the top of the team, but he commits a high number of turnovers. I ran all of these statistics on five teams: Gonzaga, St. Mary's, Utah, Virginia, and BYU. Dastrup has the second most turnovers per 40 minutes, second only to Jacob Larsen of Gonzaga, who averages around the same number of minutes as Dastrup. In conclusion, according to the statistics, Dastrup shoots well and does a lot of good things for the team, but he commits a very high number of turnovers. So, while he has great moments, he can be classified as a high risk/high reward type player. This may be why the coaches choose to not play him as many minutes as other bigs such as Childs, Worthington, and Nixon.
Notes on BYU and Other Teams
- The five teams that I studied are Gonzaga, St. Mary's, BYU, Utah, and Virginia. I decided to study the three top teams in the WCC and Utah because of their local ties. The final team I decided to study was Virginia because they are the number one team in the nation.
- I gathered statistics on team effective field goal percentage, as well as for the individual players. The teams in order of best to worst EFG are St. Mary's (58.50%), Gonzaga (57.72%), BYU (54.37%), Utah (54.00%), and Virginia (52.94%). Virginia's 52.94% is interesting since they are the number one team in the nation. They really prove that shooting and offense is not the only important part of basketball. According to the KenPom ratings, they have the number one defense in the nation.
- An interesting note is that many of the "top" shooting players on these teams average very few minutes (i.e. Jacob Larsen (Gonzaga), Jordan Hunter (St. Mary's), Jay Huff (Virginia), Payton Dastrup (BYU) . This shows that there are many other aspects to the game that are just as important, if not more important than shooting.
- The only player who leads his team in turnovers, but still plays a lot of minutes is St. Mary's Emmett Naar. Naar and Virginia's Marco Anthony are the only guards out of the five teams, that lead their team in turnovers. The difference seems to be that while Emmett Naar commits a high number of turnovers, he still has a high assist to turnover ratio as he averages over 9 assists per 40 minutes.
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